Thursday, November 19, 2015

Venue:Rm 202, Centre for Humanities and Social Sciences Education, NYMU

About the theme

How does the brain control behavior? What do neural circuits compute? The field of
cognitive neuroscience is thriving thanks to advances in neuroanatomy,
neurophysiology, neuroimaging, and cognitive psychology. Given the rich set of
empirical observations aggregated from these fields, an emerging challenge is to
provide a unified theory that relates different levels of analysis, explaining how neural
systems in the brain give rise to intelligent human behavior.
Computational cognitive neuroscience addresses the above questions by studying
neural representations and mechanisms from a theoretical perspective. It can offer
new insights beyond brain-behavior correlations. One example is the application of
machine learning/pattern recognition techniques to brain data for understanding
neural representations and for developing brain-computer interfaces. Another example
is the class of neural models that construct system-level architectures from the first
principles, such as local computation and competitive normalization. These
computational models can quantitatively simulate cognitive functions using plausible
neural mechanisms and explain seemingly conflicting data in a coherent framework.
In this presentation, differences among computational approaches in (cognitive)
neuroscience will be contrasted. The past, present, and future of computational
cognitive neuroscience will also be discussed.